n mix results

N - mixture models by species

modelling N by site to get relative abundance

abundance by site will be used as a cov on predator occupancy

7 models evaluated, dot, jdt + jdtSQ, lure + jdt + jdtSQ

Species:      Chipmunk

Metadata Summary:

N_sites	N_counts	N_detections	rep_period	iterations	burnin	thin
127	221	129	7 days	120000	20000	10

Detections by Year:

Yr	2016	2017	2018	2019	2020
sites	19	31	19	32	26
detections	15	31	14	26	43
N.dot.model	10	16	7	8	22

WAIC

Models by WAIC:

model	description	WAIC	N.total.est
fm7	counts	4.060804	127
fm5	jdt + jdtSq	830.680975	59
fm6	lure + jdt + jdtSq	831.757572	62
fm2	jdt	857.470979	61
fm4	lure + jdt	858.315210	67
fm3	lure	859.204048	60
fm1	dot	865.500876	63

Model summaries:

model: fm1

dot

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
p[1]	NA	1486	0.052	0.046	0.01	0.09	0	0.9977
p[2]	NA	4787	0.076	0.07	0.04	0.11	0	1.001
p[3]	NA	4902	0.053	0.047	0.02	0.08	0	1.001
p[4]	NA	7512	0.124	0.119	0.07	0.17	0	1.001
p[5]	NA	4250	0.064	0.062	0.04	0.09	0	1.001
lambda[1]	NA	162	1.122	0.566	0.22	1.65	0	1.0013
lambda[2]	NA	5123	0.752	0.637	0.37	1.11	0	1.001
lambda[3]	NA	3172	0.496	0.342	0.13	0.81	0	1.0009
lambda[4]	NA	9210	0.271	0.22	0.10	0.42	0	1.001
lambda[5]	NA	4293	0.991	0.867	0.51	1.44	0	1.001
N[66]	NA	5684	1.201	err	1.00	2.00	err	err
N[100]	NA	10000	0.002	err	0.00	0.00	err	err
N[81]	NA	9382	1.024	err	1.00	1.00	err	err
N[68]	NA	4898	1.478	1	1.00	2.00	0	1.0001
N[33]	NA	7970	1.143	err	1.00	2.00	err	err

p[1]

p[2]

p[3]

p[4]

p[5]

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[66]

N[100]

N[81]

N[68]

N[33]

model: fm2

jdt

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	jdt	9017	0.206	0.198	0.05	0.38	0.13548	0.9789
alpha0	NA	4853	-2.666	-2.654	-2.91	-2.42	0	1.001
lambda[1]	NA	9430	0.572	0.485	0.24	0.87	0	1.001
lambda[2]	NA	8256	0.777	0.726	0.42	1.10	0	1.001
lambda[3]	NA	10000	0.399	0.324	0.14	0.63	0	1.001
lambda[4]	NA	8344	0.366	0.335	0.15	0.55	0	1.001
lambda[5]	NA	7705	0.961	0.857	0.55	1.35	0	1.001
N[64]	NA	10000	0.034	err	0.00	0.00	err	err
N[27]	NA	9541	2.016	2.002	1.00	3.00	0	1.0006
N[75]	NA	10000	0.064	err	0.00	0.00	err	err
N[30]	NA	9529	1.903	2.002	1.00	3.00	0	1.0005
N[101]	NA	9535	0.016	err	0.00	0.00	err	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[64]

N[27]

N[75]

N[30]

N[101]

alpha relationship

model: fm3

lure

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	lure	9307	-0.119	-0.106	-0.31	0.05	0.60432	0.856
alpha0	NA	4900	-2.643	-2.64	-2.88	-2.39	0	1.001
lambda[1]	NA	9201	0.575	0.496	0.24	0.88	0	1.001
lambda[2]	NA	7998	0.746	0.693	0.41	1.05	0	1.001
lambda[3]	NA	9341	0.388	0.333	0.14	0.62	0	1.001
lambda[4]	NA	8568	0.368	0.325	0.16	0.56	0	1.001
lambda[5]	NA	7748	0.960	0.895	0.54	1.36	0	1.001
N[9]	NA	9611	1.133	err	1.00	2.00	err	err
N[105]	NA	8904	2.031	err	1.00	3.00	err	err
N[115]	NA	9512	0.089	err	0.00	0.00	err	err
N[83]	NA	10000	0.094	err	0.00	0.00	err	err
N[42]	NA	10000	0.271	err	0.00	1.00	err	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[9]

N[105]

N[115]

N[83]

N[42]

alpha relationship

model: fm4

lure + jdt

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	lureDays	5624	-0.298	-0.287	-0.50	-0.09	0.06692	0.9917
alpha[2]	julianDt	6353	0.334	0.332	0.14	0.51	0.01151	0.9997
alpha0	NA	3381	-2.782	-2.758	-3.06	-2.51	0	1.001
lambda[1]	NA	9381	0.529	0.451	0.23	0.82	0	1.001
lambda[2]	NA	7768	0.750	0.712	0.42	1.08	0	1.001
lambda[3]	NA	9556	0.410	0.362	0.15	0.65	0	1.001
lambda[4]	NA	7727	0.382	0.32	0.16	0.58	0	1.001
lambda[5]	NA	4577	1.228	1.118	0.68	1.78	0	1.001
N[58]	NA	9630	0.040	err	0.00	0.00	err	err
N[93]	NA	10000	0.064	err	0.00	0.00	err	err
N[71]	NA	9154	0.019	err	0.00	0.00	err	err
N[101]	NA	9680	0.026	err	0.00	0.00	err	err
N[99]	NA	10000	0.034	err	0.00	0.00	err	err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[58]

N[93]

N[71]

N[101]

N[99]

model: fm5

jdt + jdtSq

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	julianDt	2780	-0.568	-0.553	-0.84	-0.31	0.00519	1.0001
alpha[2]	julianDtSq	2761	0.891	0.912	0.63	1.15	0	1.001
alpha0	NA	4654	-2.746	-2.737	-3.00	-2.49	0	1.001
lambda[1]	NA	7317	0.701	0.577	0.29	1.06	0	1.001
lambda[2]	NA	8674	0.644	0.624	0.36	0.93	0	1.001
lambda[3]	NA	8596	0.422	0.35	0.15	0.67	0	1.001
lambda[4]	NA	9160	0.331	0.285	0.15	0.51	0	1.001
lambda[5]	NA	7130	0.988	0.923	0.56	1.38	0	1.001
N[41]	NA	10000	0.055	err	0.00	0.00	err	err
N[42]	NA	10000	0.255	err	0.00	1.00	err	err
N[4]	NA	9608	0.260	err	0.00	1.00	err	err
N[37]	NA	10000	1.140	err	1.00	2.00	err	err
N[49]	NA	9635	0.040	err	0.00	0.00	err	err

alpha[1]

alpha[2]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[41]

N[42]

N[4]

N[37]

N[49]

julian date relationship

model: fm6

lure + jdt + jdtSq

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha[1]	lureDays	5327	-0.211	-0.208	-0.41	-0.01	0.26016	0.9544
alpha[2]	julianDt	2609	-0.431	-0.454	-0.72	-0.14	0.06676	0.991
alpha[3]	julianDtSq	2765	0.854	0.835	0.60	1.12	0	1.001
alpha0	NA	3934	-2.819	-2.823	-3.08	-2.54	0	1.001
lambda[1]	NA	7882	0.635	0.545	0.27	0.97	0	1.001
lambda[2]	NA	8333	0.631	0.582	0.34	0.90	0	1.001
lambda[3]	NA	8832	0.423	0.351	0.15	0.67	0	1.001
lambda[4]	NA	9285	0.340	0.292	0.14	0.51	0	1.001
lambda[5]	NA	5369	1.158	1.056	0.64	1.67	0	1.001
N[112]	NA	8911	0.214	err	0.00	1.00	err	err
N[79]	NA	10000	1.078	err	1.00	1.00	err	err
N[87]	NA	10000	1.676	1	1.00	2.00	0	1.0004
N[50]	NA	9679	0.038	err	0.00	0.00	err	err
N[55]	NA	10000	0.053	err	0.00	0.00	err	err

alpha[1]

alpha[2]

alpha[3]

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[112]

N[79]

N[87]

N[50]

N[55]

model: fm7

counts

summary table

param	covariate	iters_ef	mean	mode	hdi_89pct_lower	hdi_89pct_upper	bayes_P	pct.density
alpha	counts	8949	6.936	6.22	4.88	8.89	0	1.001
alpha0	NA	10220	-7.500	-7.058	-9.12	-5.89	0	1.001
lambda[1]	NA	10000	0.986	0.861	0.44	1.50	0	1.001
lambda[2]	NA	9384	0.983	0.907	0.55	1.40	0	1.001
lambda[3]	NA	8756	0.970	0.792	0.34	1.53	0	1.0009
lambda[4]	NA	6875	0.961	0.853	0.39	1.50	0	1.001
lambda[5]	NA	10000	0.986	0.932	0.57	1.38	0	1.001
N[103]	NA	0	1.000	err	1.00	1.00	err	err
N[76]	NA	9245	0.939	0	0.00	2.00	1	err
N[27]	NA	0	1.000	err	1.00	1.00	err	err
N[96]	NA	9341	0.940	0	0.00	2.00	1	err
N[58]	NA	9344	0.950	0	0.00	2.00	1	err

alpha

alpha0

lambda[1]

lambda[2]

lambda[3]

lambda[4]

lambda[5]

N[103]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero

## Warning: Removed 50 rows containing missing values (geom_bar).

N[76]

N[27]

## Warning in cor(X, use = "pairwise.complete.obs"): the standard deviation is zero

## Warning: Removed 50 rows containing missing values (geom_bar).

N[96]

N[58]

alpha relationship